CV

Personal Statement

I am an engineering and science enthusiast committed to agility, responsibility, and teamwork. I strive to become an influential researcher in my field by consistently challenging myself and achieving my goals. My hobbies include liberal arts and languages, which I pursue passionately in my free time.

I bring a robust understanding of Semiconductor Devices, Optical Metrology, Computer Vision, and Data Science from my extensive experience in both professional environments and academic settings. My keen eye for detail, diligent work ethic, and strong project management skills make me a prime candidate for roles in Semiconductor Design and Manufacturing, Data Analytics, and Machine Learning Operations.

Education

• Ph.D. in Industrial Engineering and Management, (Expected 2028). Oklahoma State University, Stillwater, USA
  • Research Interests: Neuromorphic and In-memory Computation; Machine Learning; Deep Learning; Applied Probability.
  • Achievements:
    • Current GPA: 3.67/4.0.
    • Finalist of IISE Annual Meetings 2024 Student Paper Competition, Energy Division Track.
• M.Sc. in Automation and Electrical Engineering, (2018 - 2020). Aalto University, Espoo, Finland
  • Achievements:
    • Graduate with Honors (GPA: 4.8/5.0).
    • Dean’s List 2018-2019, 2019-2020.
  • Thesis: Realization and Verification of Deep Learning Models for Fault Detection and Diagnosis of Photovoltaic Modules. Advisors: Simo Särkkä and Khuong Nguyen-Vinh.
  • Project: Modelling and Control Methods in Renewable Energy Systems. The project focused on developing a feasible algorithm that enables photovoltaic systems to generate maximum power, specifically for application in short-haul electric vehicle charging stations. The project was funded by Fortum Oy, one of Finland’s largest energy companies.
• B.Tech. in Electronics, (2014 - 2018). Metropolia University of Applied Sciences, Helsinki, Finland.
  • Achievements:
    • Graduate with Honors (GPA 4.6/5.0).
    • Tutor of the Year (2015-2016).
  • Thesis: Safety System in Construction Industry: A protection system preventing fatal injuries by excavators in construction sites. Advisors: Matti Fisher and Jani Virtanen.
  • Project: Indoor Air Quality Sensor Fusion. The project, which was a collaborative between Metropolia University of Applied Sciences (Finland) and Osnabrück Hochschule (Germany), focused on developing an indoor air quality monitoring system. The system was designed to detect air quality, transmit and display the data to users via a custom mobile application, and trigger integrated warnings when measurements exceeded predefined thresholds.

Work Experiences

• Intel Corp. (VNAT), (04/2021 - 12/2022). Saigon Hi-Tech Park, Ho Chi Minh City, Vietnam.
  • Title: Process and Equipment Engineer & Deep Learning Scientist.
  • Responsibilities:
    • Led multiple in-house projects at VNAT focused on integrating deep learning technology for product inspection in downstream operations. Successfully completed in December 2022, these projects not only received recognition in Intel’s Q4 2022 internal audit for their impactful contributions but also were featured in Intel 2023 AI Everywhere Conference.
    • Curated tutorials and lead knowledge-sharing sessions on computer vision concepts for the Image Analytics Center of Excellence at Intel Ireland.
    • Mentored Python programming and machine learning techniques within Intel’s AI Everywhere Community, an initiative aimed at democratizing AI knowledge across the corporation.
    • Managed communications and coordinated events for NextGen Vietnam, a regional subsidiary of Intel’s NextGen Initiative focusing on integrating and developing employee competencies.
  • Projects:
    • Intelligent Inspection and Automatic Disposition System: This project focused on developing a decentralized intelligent inspection system for material handling processes in downstream operations. Preliminary results validated the system’s feasibility, drawing significant interest from multiple management levels at Intel Vietnam. Additionally, the project was showcased at the Intel 2023 AI Everywhere Conference as a leading example of AI innovation within Intel.
    • Applied Deep Learning on Inspection in Reel Packaging: The project involved developing an automated inspection program capable of detecting packaging issues, such as out-of-pocket occurrences, and promptly alerting technicians or operators to take corrective action during the reel packaging process. The project was successfully completed and formally documented as a process of record.
• First Solar Corp. (Vietnam Branch), (11/2020 - 03/2021). Dong Nam Industrial Park, Cu Chi, Vietnam.
  • Title: Manufacturing Engineer Trainee.
  • Project: The project involved the development of a standardized electroluminescence image database and process monitoring software for fault detection and diagnosis in the laser scribing process for thin-film solar panels. This software is currently employed as a reference for troubleshooting across all of First Solar’s factories.
  • Other Responsibilites: Organized technical sharing sessions on laser physics and optics in engineering, which were highly appreciated by 50+ attendees.
• Metrology Research Institute, Aalto University, (03/2019 - 12/2019). Espoo, Finland.
  • Title: Research Assistant.
  • Responsibilities:
    • Assisted the research team on an EMPIR-funded project focused on the characterization and standardization of solar cell performance. The project was successfully completed, with results published as a conference paper for the Optics in Engineering Symposium (OIE2019) in the Optical Review journal by Springer.
• Noiseless Acoustics Oy, (03/2018 - 11/2018). Helsinki, Finland.
  • Title: Electronics Manufacturing and Test Engineer
  • Responsibilities:
    • Developed testing modules for the NL Camera product and performed reliability analysis using the Failure Mode and Effects Analysis (FMEA) methodology. The modules and analysis were successfully implemented, significantly contributing to the product’s reliability improvements.
    • Implemented an Inventory Management System that streamlined tracking products across multiple stages (in-progress, finished, reworked) and component stocks.
    • Assisted in the production of the company’s principal product, the NL Camera, enabling the company to meet its production quota and address growing market demand.

Skills

• Languages: Vietnamese; English (IELTS Certified C1 level).
• Technical Skills: Python; MATLAB; LabVIEW; Arduino, LaTEX; SAS; SAS JMP.
• Technical Knowledges: Computer Vision; Data Science; Semiconductor Engineering; Optical Metrology; Power Electronics.
• Soft Skills: Project Management, Event Planning, Public Speaking.

Publications

• Books and Articles:

  • SplitVAEs: Decentralized scenario generation from siloed data for stochastic optimization problems in 2024 IEEE International Conference on Big Data (BigData).

  • The Lynchpin of In-Memory Computing: A Benchmarking Framework for Vector-Matrix Multiplication in RRAMs in 2024 ACM International Conference on Neuromorphic Systems (ICONS 2024).
  • Deep Learning Models for Fault Detection and Diagnosis in Photovoltaic Modules Manufacture in 2023 IEEE Conference on Artificial Intelligence (CAI).
  • Case Study: Utilising of Deep Learning Models for Fault Detection and Diagnosis of Photovoltaic Modules to Improve Solar Energy Constructions’ O&M Activities Quality in Information Systems Research in Vietnam (Volume 2), Springer, 2023.
  • Measurement setup for differential spectral responsivity of solar cells in Optical Review, Springer, 2020.
• Theses:
  • Realization and Verification of Deep Learning models for Fault Detection and Diagnosis of Photovoltaic Modules, Master Thesis, Aalto Learning Center, 2020.
  • Safety System in Construction Industry: A protection system preventing fatal injuries by excavators in construction sites, Bachelor Thesis, Open Repository of Universities of Applied Sciences, 2018.

Teachings

• Aalto University, Espoo, Finland
  • Teaching and Exercises Assistant, (03/2019 - 06/2019), Sensors and Measurement Methods.
• Master Thesis Advisor
  • (01/2022 - 06/2022), Crown-of-Thorns Starfish detection using YOLOv5, authored by Phuong Truong.
  • (09/2023 - 08/2024) Image Similarity Assessment for Product Quality Assurance by Khoa Nguyen.
• Visiting Lecturer
  • (01/2023) How to make frames and infer people - A lecture in Optics and Computer Vision in RMIT University Vietnam.